code: def normalize(
      audio: torch.Tensor, target_level: int = -25
  ) -> torch.Tensor:
      """Normalize the signal to the target level."""
      rms = rms_f(audio)
      scalar = 10 ** (target_level / 20) / (rms + EPS)
      audio = audio * scalar.unsqueeze(1)
      return audio
  
imports: from dataclasses import dataclass, fields, replace
  import json
  from pathlib import Path
  import random
  import typing
  import numpy
  import torch
  from .info_audio_dataset import InfoAudioDataset, get_keyword_or_keyword_list
  from ..modules.conditioners import ConditioningAttributes, SegmentWithAttributes, WavCondition
label_desc: Use image node_id 2 for calling a global function with example usage: normalize(audio, target_level) and returns: audio